Mud pulse telemetry preamble for sequence detection and channel estimation

ABSTRACT

A method and system of mud pulse telemetry uses a preamble having a number of periods of a synchronization sequence followed by a single period of a channel estimation sequence. The synchronization may be characterized by a generally flat frequency spectrum, and the channel estimation sequence may be characterized by a low cross-correlation with said synchronization sequence. The sequences may be generated from a set of nonrepeating discrete sequences. The preamble may be suitable for both sequence detection and channel estimation, satisfy all the physical and/or electronic constraints of the system, and allow for fast convergence of an adaptive channel tracking or equalization system.

PRIORITY

The present application is a U.S. National Stage patent application ofInternational Patent Application No. PCT/US2015/054667, filed on Oct. 8,2015, the benefit of which is claimed and the disclosure of which isincorporated herein by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates generally to oilfield equipment, and inparticular to downhole tools, drilling and related systems andtechniques for drilling, completing, servicing, and evaluating wellboresin the earth. More particularly still, the present disclosure relates totelemetry systems and methods.

BACKGROUND

Hydrocarbon drilling and production operations demand a great quantityof information relating to parameters and conditions downhole. Suchinformation may relate characteristics of the earth formations traversedby the wellbore, along with the size and configuration of the wellboreitself. The collection of information relating to conditions downholemay be termed “logging.”

Operators often log a wellbore during the drilling process, therebyeliminating the necessity of removing the drilling assembly to insert awireline logging tool to collect the data. Data collection duringdrilling also enables the operator to make accurate modifications orcorrections as needed to steer the well or optimize drilling performancewhile minimizing down time. Measurement-While-Drilling (MWD) and/orLogging-While-Drilling (LWD) tools and techniques allow measurementand/or logging of various conditions within the wellbore and/or thesurrounding rock formations during drilling operations. MWD/LWD toolsmay employ a variety of sensors to sample and aggregate digital valuesfor continuous real-time telemetering to the surface during drillingoperations. The transmission scheme and channel medium may vary.

Mud pulse telemetry is one of the most common methods used to send datafrom the bottom of a well to the surface while drilling. Mud pulsetelemetry uses drilling fluid that is circulated through the well duringdrilling as a communication channel. That is, the column of drilling mudthat is pumped down through the drill string becomes a medium forsending data. Pressure pulses generated by a telemetry transmitter at abottom hole assembly (BHA) send information to the well surface. Inpositive-pulse systems, a valve or other form of flow restrictor createspressure pulses in the fluid flow by adjusting the size of aconstriction in the drill string. In negative-pulse systems, a valvecreates pressure pulses by releasing fluid from the interior of thedrill string to the annulus. In both system types, the pressure pulsespropagate at the speed of sound through the drilling fluid to thesurface, where they may be detected various types of transducers.

Data transfer rates in mud pulse telemetry systems tend to be relativelylow, on the order of 30 bits per second in shallow wells and ten bitsper second in deep wells of actual downhole data. The transmissionchannel is bandwidth limited and may have noise created by drillingpumps, cutting action of the drill bit, and other sources. The downholetelemetry transmitter may also have physical and electronic constraints,resulting in a low, or even negative (as measured in dB),signal-to-noise ratio (SNR).

Attempts to increase data transfer rates may result in intersymbolinterference (ISI), a form of distortion of a signal in which one datasymbol interferes with one or more subsequent symbols, causingsuccessive symbols to “blur” together. The presence of ISI in the mudpulse telemetry system may introduce errors at the telemetry receiver.

One way to mitigate the effects of ISI is to apply adaptiveequalization, channel tracking, and/or error correcting codes at thetelemetry receiver, that, broadly speaking, attempts to undo the effectsof the channel by applying an inverse filter. Adaptive equalization andadaptive channel tracking may require a good estimation of the channelimpulse response, so that an inverse of the channel impulse response maybe applied to the received signal to reconstruct the original signal. Achirp signal, a frequency stepped signal, a pseudo random sequence, or abinary pseudo random signal may be used as a reference to estimate thechannel impulse response either in the time domain, usingcross-correlation, or in the frequency domain. Divergence of channeltracking or adaptive equalization, with concomitant data errors, mayoccur if the initial estimate of the channel impulse response is too farfrom the correct solution.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are described in detail hereinafter with reference to theaccompanying figures, in which:

FIG. 1 is an elevation view in partial cross section of a MWD/LWD systemthat employs mud pulse telemetry according to an embodiment;

FIG. 2 is a diagram that illustrates an exemplary binary signal producedby the system of FIG. 1 according to an embodiment, illustrating highand low pulses of various pulse widths as measured in bit widths;

FIGS. 3A and 3B are a flow chart of a method for generating a mud pulsetelemetry preamble according to an embodiment, for use in the system ofFIG. 1;

FIG. 4 is an upper level functional block diagram of an exemplarypseudonoise generator, according to an embodiment, for use in the systemof FIG. 1;

FIG. 5 is a diagram that illustrates a technique for generating a set ofdiscrete, nonrepeating pulse width sequences, according to anembodiment, for use in the system of FIG. 1;

FIG. 6 is a diagram that illustrates a technique for detecting apreamble generated according to the method of FIGS. 3A and 3B accordingto an embodiment, for use in the system of FIG. 1;

FIG. 7 is a diagram that illustrates a technique for detecting apreamble generated according to the method of FIGS. 3A and 3B accordingto an embodiment, for use in the system of FIG. 1; and

FIG. 8 is a diagram that illustrates a technique for detecting apreamble generated according to the method of FIGS. 3A and 3B accordingto an embodiment, for use in the system of FIG. 1.

DETAILED DESCRIPTION

The present disclosure may repeat reference numerals and/or letters inthe various examples. This repetition is for the purpose of simplicityand clarity and does not in itself dictate a relationship between thevarious embodiments and/or configurations discussed. Further, spatiallyrelative terms, such as “beneath,” “below,” “lower,” “above,” “upper,”“uphole,” “downhole,” and the like, may be used herein for ease ofdescription to describe one element or feature's relationship to anotherelement(s) or feature(s) as illustrated in the figures. The spatiallyrelative terms are intended to encompass different orientations of theapparatus in use or operation in addition to the orientation depicted inthe figures.

FIG. 1 shows an exemplary MWD/LWD system 100 according to one or moreembodiments. MWD/LWD system 100 employs a signal preamble that can beused for both the detection/data synchronization and channel estimationof the downhole mud pulse telemetry system. More specifically, thedisclosed preamble combines both the periodicity needed for detectionand synchronization and the randomness needed for channel estimation,yet allows flexibility to comply with all the mechanical and/orelectronic constraints of MWD/LWD system 100, as described in greaterdetail hereinafter. Good initial channel estimation may allow adaptiveequalization or adaptive channel tracking at the telemetry receiver tocommence the adaptation process from a solution that is close to thefinal solution, thereby allowing good data detection with minimum errorsfrom the beginning, as well as preventing divergence of the channeltracking or the equalization that could otherwise happen if the initialchannel response estimate is too far from the correct solution.Accordingly, MWD/LWD system 100 may allow an accurate detection oftransmitted data even in a very noisy environment.

Referring to FIG. 1, MWD/LWD system 100 may include a drilling platform102. Platform 102 may be equipped with a land derrick 104, which maysupport a hoist 106. However, MWD/LWD system 100 may be used inassociation with drilling rigs deployed on offshore platforms,semi-submersibles, drill ships, or any other drilling system for forminga wellbore.

Drilling of a well may be carried out by a string of drill pipesconnected together by joints 107 to form a drill string 108. Hoist 106may suspend a top drive 110 that may be used to rotate the drill string108 and to lower drill string 108 through a wellhead 112. However, aswivel, rotary table and kelly joint, or other suitable arrangement, maybe used in lieu of or in addition to top drive 110.

A drill bit 114 may be connected to the lower end of drill string 108.Drill bit 114 may be rotated by rotating drill string 108, by use of adownhole motor near the drill bit (illustrated as part of bottom holeassembly (BHA) 132 described below), or by both methods. Drilling fluidmay be pumped by mud pump 116 through flow line 118, stand pipe 120,goose neck 124, top drive 110, and down through drill string 108 at highpressures and volumes to emerge through nozzles or jets (notspecifically illustrated) in drill bit 114. The drilling fluid may thentravel back up the wellbore via the annulus 126 formed between theexterior of drill string 108 and the wellbore wall 128, through ablowout preventer (not specifically shown), and into a mud pit 130 onthe surface. On the surface, the drilling fluid may be cleaned andrecirculated by mud pump 116. The drilling fluid may function to coolthe drill bit 114, to carry cuttings from the base of the bore to thesurface, and to balance the hydrostatic pressure in the rock formations.

In wells employing mud pulse telemetry for MWD/LWD, BHA 132 may includevarious downhole tools that collect data regarding the formationproperties and/or various drilling parameters. The downhole tools arecoupled to a downhole telemetry transmitter 134, which may be part ofBHA 132, that transmits the data to the surface. In one or moreembodiments, telemetry transmitter 134 may modulate a resistance todrilling fluid flow to generate pressure pulses that propagate at thespeed of sound within the drilling fluid to the surface.

A telemetry receiver 131 may be located at the surface of the well. Inone or more embodiments, telemetry receiver 131 may include variouspressure transducers, such as transducers 136, 138 and 140, a digitizer142, and a data processor 144. Transducers 136, 138, 140 may convert thetransmitted pressure signal into electrical signals, which may besampled by signal digitizer 142 (e.g., an analog to digital converter).While three transducers 136, 138 and 140 are illustrated, a greater orlesser number of transducers may be used in particular situations.Digitizer 142 may supply a digital representation of the pressuresignals to a data processor 144. Data processor 144 may operate inaccordance with software (which may be stored on a computer-readablestorage medium) to process and decode the received signals. Theresulting telemetry data may be further analyzed and processed togenerate a display of useful information. For example, an operator mayobtain and monitor bottom hole assembly position and orientationinformation, drilling parameters, and formation properties.

Telemetry transmitter 134 may generate a traveling pressure signalrepresentative of measured downhole parameters. In an ideal system, eachand every pressure pulse created downhole propagates uphole and isreadily detected by a transducer at the surface. However, drilling fluidpressure may fluctuate significantly and contain noise from severalsources (e.g., bit noise, torque noise, and mud pump noise). Bit noisemay be created by vibration of the drill bit during the drillingoperation. Torque noise may be generated downhole by the action of thedrill bit sticking in a formation, causing the drill string to torqueup. Finally, mud pump 116 may create cyclic noise as the pistons withinthe pump force the drilling fluid into drill string 108.

For this reason, in one or more embodiments, drilling system 100 maycontain a dampener or desurger 152 to reduce noise. Flow line 118 maycouple to a drilling fluid chamber 154 within desurger 152. A diaphragmor separation membrane 156 may separate the drilling fluid chamber 154from a gas chamber 158. Diaphragm 156 may oscillate with variations inthe drilling fluid pressure, thus enabling the gas chamber to expand andcontract and thereby absorb and mitigate pressure fluctuations. Althoughdesurger 152 may minimize pressure fluctuations, desurger 152 and/or mudpump 116 may also act as reflective devices. That is, pressure pulsespropagating from the telemetry transmitter 134 may reflect off thedesurger 152 and/or mud pump 116, and propagate back downhole. Thesereflections may create interference that, in some cases, adverselyaffects the ability to determine the presence of the pressure pulsespropagating from telemetry transmitter 134.

Referring to FIG. 2, telemetry transmitter 134 (FIG. 1) is arranged totransmit a signal modulated by pressure pulses 302 (which may be definedeither by a high pressure pulse or a low pressure pulse) in the drillingfluid column (the communications channel). In one or more embodiments,the signal may be modulated by differential pulse-position modulation(DPPM). However, other modulation schemes, such as pulse-positionmodulation (PPM), pulse width modulation (PWM), quadrature phase shiftkeying (QPSK), pulse amplitude modulation (PAM), or a combinationthereof, may also be used.

In an embodiment using DPPM, the width of each pulse 302 is fixed andmay be defined by a number PW, which may be a function of physicaland/or electronic constraints of the transmitter and communicationschannel. The transmitted signal is modulated by varying the timeintervals PI between successive pulses 302. Pulse intervals PI may varybetween a minimum value PI_(min) and a maximum value PI_(max). As withPW, PI_(min) and PI_(max) may be a function of physical and/orelectronic constraints of the transmitter and communications channel.

PW, PI_(min), and PI_(max) may all be further defined as integralmultiples of a fixed time duration, known as bit width (BW). This unitis also known to routineers as a chip. FIG. 2 shows an example of atransmitted signal 300 with three pulses 302 of PW=4BW separated by afirst pulse interval PI=6BW and a second pulse interval PI=3BW. Althoughpulse interval PI is described in FIG. 2 as the interval between thetrailing edge of preceding pulse and leading edge of the subsequentpulse, it may equally be defined as the interval between the leadingedges of the preceding and subsequent pulses.

An initial function of telemetry receiver 131 may be the detection thebeginning of a transmitted signal from telemetry transmitter 134. In oneor more embodiments, detection may be performed by transmitting apreamble 175 with a known digital sequence that the receiver can detectfor data synchronization. One of the challenges of mud pulse telemetryis the detection of the beginning of the transmitted sequence in a verynoisy environment. Sequence detection may require a reliable detectionalgorithm that can work even at a negative (as measured in dB)signal-to-noise ratio (SNR). Once the known digital preamble sequence isdetected, the decoding process may be commenced. In order to be abledecode with minimum errors, a good estimate of the channel impulseresponse may be required for adaptive equalization or adaptive channeltracking. Estimation of the channel impulse response may be anotherfunction of telemetry receiver 131.

Telemetry transmitter 134 and the communications channel may becharacterized by many physical and electronic constraints. For instance,the pulse width PW defining the pulses may be constrained to minimum andmaximum durations and there may be minimum and maximum delays PI_(min),PI_(max) allowed between pulses. Preamble 175 may include randomsequences “B” and “C” of digital pulses that meet all the systemconstraints of telemetry transmitter 134. In one or more embodiments, asshown in FIG. 1, preamble 175 includes a number of periods of asynchronization sequence “B” to provide enough periodicity so it can beused for sequence detection and timing synchronization, followed by achannel estimation sequence “C” to still provide ample randomness toallow a good channel impulse response estimate to be generated.

FIGS. 3A and 3B are a flow chart of a method 200 for creating mud pulsetelemetry preamble 175 according to one or more embodiments. Steps204-228 of FIG. 3A outline a method for creating synchronizationsequence “B”. Similarly, steps 234-258 of FIG. 3B outline a method forcreating channel estimation sequence C.

As previously discussed, telemetry preamble 175 may have two goals:Synchronization, determining the beginning of the transmitted preamble175 by telemetry receiver 131 as accurately as possible; and channelestimation, enabling an initial accurate estimation of the channelimpulse response by telemetry receiver 131. In order to support thesegoals, according to one or more embodiments preamble 175 ischaracterized by a sharp autocorrelation peak. Assuming that acontinuous cross-correlation of the signal received at telemetryreceiver 131 with a reference signal is calculated, a sharpautocorrelation function will aid in the detection of the exact timingof the commencement of preamble 175. Once the beginning of preamble 175is detected by telemetry receiver 131, preamble 175 may be used tocalculate the channel impulse response using a method such as LeastSquares. In order to calculate this response, an optimal signal may be aflat wide-band signal characterized by a spectrum that covers the entiretransmission band. Such a signal is also characterized by a sharpautocorrelation peak.

Referring to FIG. 3A, at step 204 initial conditions are set. A countervariable I and a variable MAX_IX are initialized to zero. At step 208, aset of discrete, non-repeating sequences of bits is iteratively createdusing random or pseudorandom generated bits. Each sequence representsone period of fixed pulses separated by varying pulse intervals PI. Aperiod is made up of a number M pulses, as described hereinafter. Fromthis set, synchronization sequence “B” may be selected as having theflattest frequency spectrum of all the sequences in the set.

In particular, for each iteration of step 208, a cost function IXrepresentative of the flatness of the frequency spectrum of thegenerated sequence is calculated at step 212. If the current costfunction IX is greater than the value presently stored in variableMAX_IX (step 216), at step 220 MAX_IX is updated to the current costfunction IX, and the current sequence is stored in a temporary sequencevariable Bf. At step 208, counter variable I is incremented by thenumber of bits generated to create the evaluated sequence, which isdescribed in greater detail below. At step 224, the cycle of steps208-220 may be repeated until each non-repeating sequence of the set hasbeen evaluated, thereby allowing selection of the synchronizationsequence “B” of maximal spectral flatness. In one or more embodiments,the set of sequences may include up to a number (2^(N)−1)/MD ofnonrepeating sequences, as described in greater detail hereinafter.

After selection of synchronization sequence “B”, a similar process maybe used to select the channel estimation sequence “C”. Referring to FIG.3B, at step 234 initial conditions are set. A counter variable I and avariable MIN_XC are initialized to zero. At step 238, sequences areagain iteratively generated from the set of discrete, non-repeatingsequences. As before, each sequence represents one period of M fixedpulses separated by varying pulse intervals PI. From this set, channelestimation sequence “C” may be selected as having the minimumcross-correlation of all the sequences in the set with respect tosynchronization sequence “B”.

In particular, for each iteration of step 238, a cross-correlation XC ofthe generated sequence with synchronization sequence “B” is calculatedat step 242. If the current cross-correlation XC is less than the valuepresently stored in variable MIN_XC (step 246), at step 250 MIN_XC isupdated to the current cross-correlation XC, and the current sequence isstored in a temporary sequence variable Cf. Also at step 238, countervariable I is incremented by the number of bits generated to create theevaluated sequence, which is described in greater detail below. At step254, the cycle of steps 228-250 may be repeated until each non-repeatingsequence of the set has been evaluated, thereby allowing selection ofthe channel estimation sequence “C” characterized by minimalcross-correlation with synchronization sequence “B”. In one or moreembodiments, the set of sequences may include up to a number(2^(N)−1)/MD of nonrepeating sequences, as described in greater detailhereinafter.

According to one or more embodiments, at step 270, preamble 175 (FIG. 1)is assembled to have a number of serially repeated periods ofsynchronization sequence “B” followed by an instance of channelestimation sequence “C”. According to one or more embodiments, preamble175 enables a reliable detection of the beginning of a transmittedsignal with high accuracy in a noisy environment, which may beaccomplished by including within preamble 175 several serially repeatedperiods of synchronization sequence “B”. The number and length ofsynchronization sequences “B” may be set so noise may be sufficientlyaveraged but the frequency spectrum will remain as flat as possible. Thenumber of repeated periods of synchronization sequence “B” is acompromise between the need for accurate detection of the data statingpoint and the accuracy of the channel estimation. Assuming the totallength of preamble 175 to be limited by the allowed system overhead,increasing the number of periods of synchronization sequence “B”improves the accuracy of the determination of the data starting pointbut lowers the resolution of the initial channel estimate. If the totalnumber of periods in preamble 175 is N_(P), there may be N_(P)−1 serialinstances of synchronization sequence “B” followed by a single channelestimation sequence C. In one or more embodiments, preamble 175 may havefive periods, consisting of four synchronization sequences “B” followedby a single channel estimation sequence C. However, preamble 175 mayconsist of a different number of periods N_(P) as appropriate.

Generation of the set of discrete, non-repeating sequences of steps 208and 238 is now described in greater detail. FIG. 4 illustrates theoperation of a pseudonoise (PN) sequence generator 310, which in one ormore embodiments may be implemented by a linear feedback shift register(LFSR). PN sequence generator 310 may generate a pseudorandom sequenceof bits by connecting the linear feedback shift register based on theproperties of a primitive polynomial—a polynomial is that it is evenlydivisible only by itself and 1. An example of a primitive polynomial oforder 18, which is implemented by PN sequence generator 310 of FIG. 4,is x¹⁸+x³+1. A notable feature of a PN sequence that is generated by aprimitive polynomial of order N is that the sequence does not repeatuntil the entire N^(th) order sequence has been generated. In otherwords, the period of the pseudorandom sequence in bits is 2^(N)−1. Inthe example of FIG. 4, the period of the sequence is 2¹⁸−1, or 262,143bits. In steps 208 and 238 of FIGS. 3A and 3B, counter variable I may beincremented for each iteration of, or bit produced by, PN sequencegenerator 310.

Although FIG. 4 illustrates a PN sequence of the 18th order, anysuitable order may be used as appropriate. In one or more embodiments,PN sequence generator 310 may be implemented using MATLAB® or othersimulation software. Moreover, other techniques for generating a randomor pseudorandom sequence of bits may also be used.

FIG. 5 illustrates the process of resolving the pseudorandom sequence of2^(N)−1 bits into a set of sequences of M fixed pulses separated byvarying pulse intervals PI. First, the pseudorandom sequence of 2^(N)−1bits generated by PN sequence generator 310 may be split to groups of Dbits, where the number D is based on the physical and/or electricalconstraints of telemetry transmitter 134 (FIG. 1). For example, if theminimum pulse interval PI_(min) is 4 chips and the maximum pulseinterval PI_(max) is 10 chips, there are seven different options ofpulse intervals requiring three bits to describe. In general, the numberof bits needed may be given by Equation 1:D=ceil(log₂(PI _(max) −PI _(min)))  Eq. 1where ceil(x) is a function that selects the smallest integer largerthen x. Splitting the pseudorandom sequence of 2^(N)−1 bits into groupsof D consecutive bits results in a non-repeating series of (2^(N)−1)/Dgroups of D bits.

In one or more embodiments, each group of D bits may be expressed as adecimal number D_(x) and may define the next pulse interval PI measuredin chips. Thus, in the above example of PI_(min)=4 and PI_(max)=10, thebit combination “0 0 0” (D_(x)=0) represents a PI of 4 chips, “0 1 1”(D_(x)=3) represents a PI of 7 chips, and “1 1 1” (D_(x)=7) represents aPI of 10 chips, etc.

In order to meet all the physical and/or electrical constraints oftelemetry transmitter 131 and/or the communications channel, each numberD_(x) may be compared to the maximum and minimum pulse intervals. IfPI_(min)≤D_(x)≤PI_(max), the number D_(x) may be retained and used todefine the next pulse interval PI; if D_(x) falls outside of thePI_(min) and PI_(max) limits, that number D_(x) may be discarded. Thisprocess may be repeated until the entire sequence (2^(N)−1)/D of numbersD_(x) has been evaluated or the total number of pulses needed to definesynchronization sequence “B” or channel estimation sequence “C” has beengenerated. Because some numbers D_(x) may be discarded, the total usablepulse intervals PI generated may be less than (2^(N)−1)/D. An example ofa discarded D_(x) is illustrated in FIG. 5.

Next, the pulse intervals PI generated in the step above may be furthersubdivided to define a set of sequences of M pulse intervals PI. Thenumber M represents the number of pulses in each sequence and isreferred to as one period. In one or more embodiments, the value M maybe selected based on the maximum expected channel impulse responselength. Because preamble 175 may be used for channel impulse responseestimation, the period M measured in time should be longer than themaximum expected channel impulse response length L. The maximum expectedchannel impulse response length L may be determined by the number ofreflections in drill string 108 (FIG. 1) defining the communicationschannel. Empirical data from different wells show that the maximumexpected channel impulse response length L is usually less than twoseconds. There may be reflections that arrive after two seconds, butsuch delayed reflections are usually much attenuated compared to theinitial reflections. In order to be able to obtain a good initialchannel impulse response estimate in a very noisy environment, in one ormore embodiments, a period length of at least five times the maximumexpected channel impulse response length L may be selected.

Steps 212, 216, and 220 of FIG. 3A—the selection of synchronizationsequence “B”—are now described in greater detail. There are severalcriteria that can be used to select the best synchronization sequence“B” from the generated set of discrete, non-repeating sequences. In oneor more embodiment, the criterion of maximum spectral flatness of thesequence in the frequency domain may be used. In the time domain, thiscriterion translates into minimal width of the autocorrelation function,with the best synchronization sequence “B” being characterized by anautocorrelation function approaching a delta function. The flatness ofthe spectrum is also appropriate for good channel estimation.

There are many ways to calculate the flatness of the spectrum of a givensequence. In one or more embodiments, a normalized Fourier Transform ofthe sequence autocorrelation AX_(n)(k) may be first calculated, where Pis the length or period of the sequence:

$\begin{matrix}{{X(k)} = {\sum\limits_{n = 0}^{P - 1}{x_{n}e^{{- j}\; 2\pi\;{{nk}/P}}}}} & {{Eq}.\mspace{14mu} 2} \\{{{AX}_{n}(k)} = {\frac{{X(k)}*{X(k)}^{*}}{{X}^{2}}.}} & {{Eq}.\mspace{14mu} 3}\end{matrix}$Next the “Entropy” in frequency domain may be calculated:

$\begin{matrix}{{IX} = {- {\sum\limits_{k = 0}^{P - 1}{{{AX}_{n}(k)}*{\log\left( {{AX}_{n}(k)} \right)}}}}} & {{Eq}.\mspace{14mu} 4}\end{matrix}$Equation 4 may be used as a cost function to select the best sequence.As described above with respect to FIG. 3A, cost function IX may becalculated for each new generated sequence of the set of non-repeatingsequences, and the sequence with the maximum cost function IX may beselected as the best synchronization sequence “B”.

Steps 242, 246, and 250 of FIG. 3B—the selection of channel estimationsequence “C”—are now described in greater detail. A cross-correlationfunction XC may be calculated for each new generated sequence of the setof non-repeating sequences, and the sequence with the minimum (i.e.,more negative) cross-correlation XC with synchronization sequence “B”may be selected as the best channel estimation sequence “C”. Thenormalized cross-correlation XC between synchronization sequence “B” andcurrently evaluated sequence may be calculated as follows:

$\begin{matrix}{{XC}_{C} = \frac{\sum\limits_{i = 0}^{P - 1}{{B(p)}*{C(p)}}}{\left( {\sum\limits_{i = 0}^{P - 1}{{B(p)}^{2}{\sum\limits_{i = 0}^{P - 1}{C(p)}^{2}}}} \right)^{1/2}}} & {{Eq}.\mspace{14mu} 5}\end{matrix}$

Having thus described how to assemble preamble 175, the use of preamble175 for sequence detection at telemetry receiver 131 (FIG. 1) is nowdescribed. Detection of preamble 175 uses the periodicity provided bythe repeated periods of synchronization sequence “B”. In one or moreembodiments, telemetry receiver 131 may include a correlator (notexpressly illustrated). A number of autocorrelation calculations may beperformed by the correlator using sections of the signal received bytelemetry receiver 131 that are multiples of the period length P inchips of synchronization sequence “B”. The autocorrelation equation maybe expressed as:

$\begin{matrix}{{{cor}(k)} = \frac{\left( {\sum\limits_{i = 0}^{P - 1}{x_{i}x_{i - {kP}}}} \right)^{2}}{\sum\limits_{i = 0}^{P - 1}{x_{i}^{2}{\sum\limits_{i = 0}^{P - 1}x_{i - {kP}}^{2}}}}} & {{Eq}.\mspace{14mu} 6}\end{matrix}$where k ranges between 1 and N_(P)−2, and N_(P) is the number of periodsin preamble 175.

FIG. 6 shows sections S0, S1, S2, S3, S4, etc. of the received signal340 that are being autocorrelated as described above for the case ofN_(P)=5. Each correlation is P samples long. When preamble 175 isanalyzed at the corellator, sections S0, S1, S2, S3, S4, etc. willoverlap but not necessarily align with the received synchronizationsequences “B”.

Other autocorrelation combinations may also be calculated, such as S1with S2, S2 with S3, and so on. Altogether there

$\quad\begin{pmatrix}N_{P} \\2\end{pmatrix}$different autocorrelations that may be calculated. An advantage of usingthe autocorrelation calculations cor(1), cor(2), cor(3), etc. ofEquation 6 and FIG. 6 is that the sum of these autocorrelations may havea steep downward slope, which be used for an accurate detection of thepreamble end point as described below.

Referring now to FIG. 7, the autocorrelation calculations of Equation 6,cor(1), cor(2), cor(3), etc., may then be averaged together by thecorrelator as follows:

$\begin{matrix}{{Corsum} = {\frac{1}{\left( {N_{P} - 2} \right)}{\sum\limits_{k = 1}^{N_{P} - 2}{{cor}(k)}}}} & {{Eq}.\mspace{14mu} 7}\end{matrix}$In the ideal case, as preamble 175 of received signal 340 is analyzed,the correlator Corsum output 345 will behave as illustrated in FIG. 7.The Corsum output 345 will stay close to 0 as long as received signal340 contains only noise. Once the second period of preamble 175 starts,the Corsum output 345 will start to rise linearly until the end of thelast period of synchronization sequence “B”, at which point the Corsumoutput 345 will reach approximately unity. Then, during the channelestimation sequence “C”, the Corsum output 345 will rapidly fall to somelow value that depends on the cross-correlation between synchronizationsequence “B” and channel estimation sequence “C”.

The shape of the Corsum output 345 curve may be used to estimate the endof the preamble and the start of MWD/LWD data in various ways. In one ormore embodiments, two thresholds may be defined—a positive threshold(P_threshold) and a negative threshold (N_threshold). The correlator maybe considered as a state machine, which starts in a “no signal” state(state 0). In the “no signal” state, the correlator looks for the Corsumoutput 345 to pass above P_threshold. Once the Corsum output 345 passesthe P_threshold, the state switches to “preamble” (state 1). Thereafter,the correlator looks for the Corsum output 345 to drop belowN_threshold. The Corsum output 345 dropping below N_threshold signalsthe end of preamble 175. The state switches to “preamble end” (state 2)and then may return to the “no signal” state.

FIG. 8 illustrates an exemplary case of the Corsum behavior with asimulated received signal 340. The thresholds in this example areP_threshold=0.85 and N_threshold=−0.1. As can be seen, there is a noiseperiod until approximately sample 60000, and the corellator Corsumoutput 345 and the correlator state 350 remain at zero. Preamble 175starts at approximately sample 60000. The corellator Corsum output 345rises slowly to almost 1.0, and as Corsum output 345 reachesP_threshold=0.85, correlator state 350 changes to state 1. Atapproximately sample 65000, channel estimation sequence “C” begins. TheCorsum output 345 begins falls sharply to approximately −0.3, and whenthe Corsum output 345 reaches N_threshold=−0.1, and correlator state 350changes to state 2, and then back to state 0.

Once preamble 175 is detected at telemetry receiver 131 (FIG. 1),preamble 175 may be used to estimate the impulse response of thecommunications channel (drill pipe 108). There are many ways to do thisestimation both in the frequency domain and the time domain. In one ormore embodiments, a Least Squares (LS) mathematical method may be usedto calculate the pseudo inverse of the correlation matrix of preamble175 and multiply the pseudo inverse by the received signal to produce anestimated channel impulse response as follows.

Assume the entire preamble 175 is defined by the sequence [x₀, x₁, . . ., x_(N)], where N=P*N_(P), P is the length of one period, and N_(P) isthe number of periods in preamble 175. Further, assume that the maximumchannel impulse response is defined by length L. As discussed earlier,the value L may be determined empirically, using simulations, orcalculated based on a physical model of the communications channel.

The following matrix may be defined:

$\begin{matrix}{A = \begin{bmatrix}{0,} & {0,} & \ldots & {0,} & {x_{0},} & {x_{1},} & \ldots & x_{N - L} \\{0,} & \ldots & {0,} & {x_{0},} & {x_{1},} & \ldots & \ldots & x_{N - L + 1} \\\; & \; & \; & \; & \vdots & \; & \; & \; \\{x_{0},} & {x_{1},} & \ldots & \ldots & \ldots & \ldots & \ldots & x_{N - 1}\end{bmatrix}} & {{Eq}.\mspace{14mu} 8}\end{matrix}$Next, the autocorrelation matrix R=A*A^(T) may be generated. Thepseudo-inverse of A is A_(inv)=R⁻¹A. Once the end point of preamble 175is determined as described above, the last N samples, referred to hereinas Y, may be multiplied by A_(inv), as shown in Equation 9. The result,h_(channel), is the channel impulse response estimate:h _(channel) =A _(inv) *Y  Eq. 9

Thus, as described herein, a mud pulse telemetry system and method thatemploys preamble 175 may be suitable for both sequence detection andchannel estimation, satisfy all the physical and/or electronicconstraints of the telemetry system, and allow for fast convergence ofan adaptive channel tracking or equalization system.

Although the above description was in relation to an embodiment usingDPPM, it may be used with other modulation schemes. For example, inaddition to varying the pulse intervals PI, pulse widths PW may also bemodulated to carry signal information. In such a case, each pulse widthPW and pulse interval PI may be correspond to a number D_(x) thatsatisfies the criteria for minimum and maximum pulse widths PW_(min),PW_(max) and minimum and maximum pulse intervals PI_(min), PI_(max),respectively. Synchronization sequence “B” and channel estimationsequence “C” may be selected, generally as described above, from a setof (2^(N)−1)/2MD of nonrepeating sequences.

In summary, a telemetry method and system have been described.Embodiments of the method of telemetry may generally include: Defining asynchronization sequence of pulses separated by varying pulse intervals,the synchronization sequence characterized by a generally flat frequencyspectrum, the synchronization sequence defining a period length P;defining a channel estimation sequence of pulses separated by varyingpulse intervals, the channel estimation sequence characterized by a lowcross-correlation with the synchronization sequence; defining a preamblehaving a number Np−1 of serially repeated periods of the synchronizationsequence followed by an instance of the channel estimation sequence; andtransmitting the preamble by a transmitter across a communicationchannel. Embodiments of the telemetry system may generally have: Atransmitter; a receiver; and a communication channel coupling thetransmitter with the receiver; the transmitter designed and arranged totransmit a signal including preamble having a number Np−1 of seriallyrepeated periods of a synchronization sequence followed by an instanceof a channel estimation sequence, the synchronization sequencecharacterized by a generally flat frequency spectrum, the channelestimation sequence characterized by a low cross-correlation with thesynchronization sequence; the receiver designed and arranged to receiveand autocorrelate the signal to identify the serially repeated periodsof the synchronization sequence and estimate an endpoint of the channelestimation sequence.

Any of the foregoing embodiments may include any one of the followingelements or characteristics, alone or in combination with each other:Selecting a total number P*Np to define a preamble length that exceeds amaximum expected impulse response length of the channel in time;generating a set of non-repetitive sequences each having a number M ofpulses separated by the number M of pulse intervals; selecting from theset the synchronization sequence having a maximally flat frequencyspectrum; selecting from the set the channel estimation sequence havinga minimal cross-correlation with the synchronization sequence;calculating an autocorrelation of each of the set to select thesynchronization sequence; defining a minimum pulse interval by a minimumnumber of chips; defining a maximum pulse interval by a maximum numberof the chips; determining a minimum number D of digital bits required toencode any number of chips ranging from the minimum number of the chipsto the maximum number of the chips; generating a series of digital bits;separating the series of digital bits by the number D to define a seriesof pulse intervals; separating the series of pulse intervals into groupsof the number M to generate the set; generating the series of digitalbits using a PN sequence generator; receiving by a receiver a signalincluding the transmitted preamble; detecting the transmitted preamble;estimating an identifiable point in the transmitted preamble;repetitively calculating autocorrelation values of the signal;identifying using the autocorrelation values the serially repeatedperiods of the synchronization sequence in the transmitted preamble;identifying using the autocorrelation values an endpoint of the instanceof the channel estimation sequence as the identifiable point in thetransmitted preamble; each of the autocorrelation values is an averageof a plurality of autocorrelations of the signal, each of the pluralityof autocorrelations having a number of samples equal to the periodlength P, the plurality of autocorrelations characterized by delays thatare multiples of the period length P; estimating an impulse response ofthe channel using the transmitted preamble; varying by the transmitterwidths of the pulses; the synchronization and channel estimationsequences each have a number M of pulses separated by the number M ofvarying pulse intervals; the synchronization sequence defines a periodlength P; a total number P*Np defines a preamble length that exceeds amaximum expected impulse response length of the channel; the transmitteris limited by a minimum pulse interval; the telemetry system furtherconstrains the varying pulse intervals above the minimum pulse interval;the transmitter is limited by a minimum pulse width and a maximum pulsewidth; the telemetry system further constrains the varying the pulsesbetween the minimum pulse width and the maximum pulse width; thereceiver is designed and arranged to calculate an estimated channelimpulse response length using the preamble; and the transmitter varieswidths of the pulses.

The Abstract of the disclosure is solely for providing the reader a wayto determine quickly from a cursory reading the nature and gist oftechnical disclosure, and it represents solely one or more embodiments.

While various embodiments have been illustrated in detail, thedisclosure is not limited to the embodiments shown. Modifications andadaptations of the above embodiments may occur to those skilled in theart. Such modifications and adaptations are in the spirit and scope ofthe disclosure.

What is claimed:
 1. A method of telemetry, comprising: defining asynchronization sequence of pulses separated by varying pulse intervals,said synchronization sequence characterized by a generally flatfrequency spectrum, said synchronization sequence defining a periodlength P; defining a channel estimation sequence of pulses separated byvarying pulse intervals, said channel estimation sequence characterizedby a low cross-correlation with said synchronization sequence; defininga preamble having a number N_(p)−1 of serially repeated periods of saidsynchronization sequence followed by an instance of said channelestimation sequence; and transmitting said preamble by a transmitteracross a communication channel.
 2. The method of claim 1 furthercomprising: selecting a total number P*N_(p) to define a preamble lengththat exceeds a maximum expected impulse response length of said channelin time.
 3. The method of claim 1 further comprising: generating a setof non-repetitive sequences each having a number M of pulses separatedby said number M of pulse intervals; selecting from said set saidsynchronization sequence having a maximally flat frequency spectrum; andthen selecting from said set said channel estimation sequence having aminimal cross-correlation with said synchronization sequence.
 4. Themethod of claim 3 further comprising: calculating an autocorrelation ofeach of said set to select said synchronization sequence.
 5. The methodof claim 3 further comprising: defining a minimum pulse interval by aminimum number of chips; defining a maximum pulse interval by a maximumnumber of said chips; determining a minimum number D of digital bitsrequired to encode any number of chips ranging from said minimum numberof said chips to said maximum number of said chips; generating a seriesof digital bits; separating said series of digital bits by said number Dto define a series of pulse intervals; and separating said series ofpulse intervals into groups of said number M to generate said set. 6.The method of claim 5 further comprising: generating said series ofdigital bits using a PN sequence generator.
 7. The method of claim 1further comprising: receiving by a receiver a signal including saidtransmitted preamble; detecting said transmitted preamble; andestimating an identifiable point in said transmitted preamble.
 8. Themethod of claim 7 further comprising: repetitively calculatingautocorrelation values of said signal; identifying using saidautocorrelation values said serially repeated periods of saidsynchronization sequence in said transmitted preamble; and identifyingusing said autocorrelation values an endpoint of said instance of saidchannel estimation sequence as said identifiable point in saidtransmitted preamble.
 9. The method of claim 8 wherein: each of saidautocorrelation values is an average of a plurality of autocorrelationsof said signal, each of said plurality of autocorrelations having anumber of samples equal to said period length P, said plurality ofautocorrelations characterized by delays that are multiples of saidperiod length P.
 10. The method of claim 7 further comprising:estimating an impulse response of said channel using said transmittedpreamble.
 11. The method of claim 1 further comprising: varying by saidtransmitter widths of said pulses.
 12. A telemetry system, comprising: atransmitter; a receiver; and a communication channel coupling saidtransmitter with said receiver; said transmitter designed and arrangedto transmit a signal including preamble having a number N_(p)−1 ofserially repeated periods of a synchronization sequence followed by aninstance of a channel estimation sequence, said synchronization sequencecharacterized by a generally flat frequency spectrum, said channelestimation sequence characterized by a low cross-correlation with saidsynchronization sequence; said receiver designed and arranged to receiveand autocorrelate said signal to identify said serially repeated periodsof said synchronization sequence and estimate an endpoint of saidchannel estimation sequence.
 13. The telemetry system of claim 12wherein: said synchronization and channel estimation sequences each havea number M of pulses separated by said number M of varying pulseintervals; said synchronization sequence defines a period length P; anda total number P*N_(p) defines a preamble length that exceeds a maximumexpected impulse response length of said channel.
 14. The telemetrysystem of claim 13 wherein: said transmitter is limited by a minimumpulse interval; and the telemetry system further constrains said varyingpulse intervals above said minimum pulse interval.
 15. The telemetrysystem of claim 13 wherein: said transmitter is limited by a minimumpulse width and a maximum pulse width; and the telemetry system furtherconstrains said varying said pulses between said minimum pulse width andsaid maximum pulse width.
 16. The telemetry system of claim 12 wherein:said receiver is designed and arranged to calculate an estimated channelimpulse response length using said preamble.
 17. The telemetry system ofclaim 13 wherein: said transmitter varies widths of said pulses.